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20242026
most citedUnmasking Deceptive Visuals: Benchmarking Multimodal Large Language Models on Misleading Chart Question Answering

1 citations · 2 across the 5 of their papers we have counts for

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cs.CL2024

FIRST: Teach A Reliable Large Language Model Through Efficient Trustworthy Distillation

KaShun Shum, Minrui Xu, Jianshu Zhang +5

Large language models (LLMs) have become increasingly prevalent in our daily lives, leading to an expectation for LLMs to be trustworthy -- - both accurate and well-calibrated (the…

cs.AI2024★ 1 cited

On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents

Jen-tse Huang, Jiaxu Zhou, Tailin Jin +6

Large language model-based multi-agent systems have shown great abilities across various tasks due to the collaboration of expert agents, each focusing on a specific domain. Howeve…